ArticleBMJ open sport & exercise medicine2024
Association between profiles of accelerometer-measured daily movement behaviour and mortality risk: a prospective cohort study of British older adults.
Article in BMJ open sport & exercise medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Synthesis and Validity of Accelerometer Devices and Methods Used in Epidemiological Studies of Physical Activity Bout Duration and Health Outcomes: A Systematic Review.Sports medicine - open · 2026Pooled it
- Digital Sleep-Wake Cycle Metrics and Dementia Prediction in Older Adults.JAMA neurology · 2026Article
- Age-Associated Differences in Paddock Locomotor Activity Among Senior Horses: A Pilot Observational Study.Animals : an open access journal from MDPI · 2026Article
- Circadian rhythm profiles derived from accelerometer measures of the sleep-wake cycle in two cohort studies.Nature communications · 2025Article
- Reallocation of time between accelerometer-derived movement behaviors, genetic susceptibility, and risk of incident dementia, mortality, and premature death: a longitudinal cohort study.The international journal of behavioral nutrition and physical activity · 2025Article
- Examining physical activity clustering using machine learning revealed a diversity of 24-hour step-counting patterns.Journal of activity, sedentary and sleep behaviors · 2024Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: We identified profiles of wake-time movement behaviours (sedentary behaviours, light intensity physical activity and moderate-to-vigorous physical activity) based on accelerometer-derived features among older adults and then examined their association with all-cause mortality. Methods: Data were drawn from a prospective cohort of 3991 Whitehall II accelerometer substudy participants aged 60-83 years in 2012-2013. Daily movement behaviour profiles were identified using k-means cluster analysis based on 13 accelerometer-assessed features characterising total duration, frequency, bout duration, timing and activity intensity distribution of movement behaviour. Cox regression models were used to assess the association between derived profiles and mortality risk. Results: Over a mean follow-up of 8.1 (SD 1.3) years, a total of 410 deaths were recorded. Five distinct profiles were identified and labelled as 'active' (healthiest), 'active sitters', 'light movers', 'prolonged sitters', and 'most sedentary' (most deleterious). In model adjusted for sociodemographic, lifestyle, and health-related factors, compared with the 'active' profile, 'active sitters' (HR 1.57, 95% CI 1.01 to 2.44), 'light movers' (HR 1.75, 95% CI 1.17 to 2.63), 'prolonged sitters' (HR 1.67, 95% CI 1.11 to 2.51), 'most sedentary' (HR 3.25, 95% CI 2.10 to 5.02) profiles were all associated with a higher risk of mortality. Conclusion: Given the threefold higher mortality risk among those with a 'most sedentary' profile, public health interventions may target this group wherein any improvement in physical activity and sedentary behaviour might be beneficial.
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